Research on Convenient and Privacy Compliant Biometric Systems
The mission of our research on Biometrics is to achieve progress towards better Biometric systems. While our work is covering numerous physiological and behavioral modality including 2D- and 3D-face recognition, iris recognition, fingerprint recognition, fingervein recognition, ear recognition and gait recognition the intention to be better has various flavors. In the first instance the research is targeting improved recognition performance, which we want to achieve by quality assessment of biometric enrolment samples. In the second instance we are concerned about development and deployment of convenient unobtrusive biometrics that can e..g. protect personal or business data that is stored on smartphones. Exploiting the embedded smartphone sensors is our strategy to deploy biometrics without any hardware costs. The third and yet very relevant instance is our work on privacy enhancing technologies such as biometric template protection and design of biometric systems according to the Privacy-by-Design principle. Our group is actively participating in international academic conferences such as ICB, BTAS and BIOSIG and contributes both to the European Association for Biometrics (EAB) and the international standardisation in ISO/IEC JTC1 SC37.
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HDA Down Syndrome Face Database
The database was used in [1] to evaluate the biometric performance of open-source and commercial face recognition systems on people
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T-shirt Face Presentation Attack (TFPA) database
The TFPA database is a database consisting of 1,608 T-shirt attacks using 100 unique presentation attack instruments (PAIs). The T-shirt
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HDA Synthetic Children Face Database
The HDA-SynChildFaces database consists of synthetic face images from 1,652 subjects and a total of 188,328 images, each subject being
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HDA Semi-synthetic Tattoo Database
HDA Semi-synthetic Tattoo Database The Hochschule Darmstadt (HDA) semi-synthetic tattoo database contains 5,500 synthetic images with tattooed subjects as well
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COLFISPOOF: A Database for Contactless Fingerprint Presentation Attack Detection Research
COLFISPOOF A Database for Contactless Fingerprint Presentation Attack Detection Research The COLFISPOOF database acquired in 2022 which contains 7,200 samples
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HDA Cross-Domain Face Database
HDA Cross-Domain Face Database The Hochschule Darmstadt (HDA) cross-domain face database contains 1,400 face images from three different domains including avatars
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HDA Doppelgänger Face Database
HDA Doppelgänger Face Database The Hochschule Darmstadt (HDA) doppelgänger database contains 400 pairs of doppelgänger images collected from multiple web sources.
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HDA Facial Makeup Presentation Attack Database
HDA Facial Makeup Presentation Attack Database Hochschule Darmstadt (HDA) facial makeup presentation attack database (HDA_MPA_DB) contains web-collected facial images of
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HDA Facial Tattoo and Painting Database
HDA Facial Tattoo and Painting Database The Hochschule Darmstadt (HDA) facial tattoo and paintings database contains 500 pairs of facial
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HDA Plastic Surgery Face Database
HDA Plastic Surgery Face Database The Hochschule Darmstadt (HDA) plastic surgery database contains facial images taken before and after five
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Presentation Attack Detection for Finger Recognition
Presentation Attack Detection for Finger Recognition Score files of the experiments using finger vein images for fingerprint presentation attack detection
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MCIS
MCIS – Multi-Class Iris Segmentation A database providing semantic segmentation labels for 500 images of the NICE.I database. Download The
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Measuring Unlinkability in Biometric Template Protection Systems
Measuring Unlinkability in Biometric Template Protection Systems Implementation of local and global unlinkability metrics for biometric template protection schemes proposed
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Multi-Biometric Template Protection Based on Bloom Filters
Multi-Biometric Template Protection Based on Bloom Filters Implementation of the feature level fusion of Bloom filter based protected templates proposed
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SIC-Gen
SIC-Gen: Synthetic Iris-Code generator A method for generation of large-scale synthetic Iris-Code databases proposed by Drozdowski et al. [1]. Code
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da/sec WDSET02 multisensor fingerprint database
WDSET02 da/sec WDSET02 multisensor fingerprint database WDSET02 is a multisensor fingerprint database obtained using optical sensors for the acquisition of
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MBASSy – Modular Biometric Authentication Service System
MBASSy (Modular Biometric Authentication Service System) Since the introduction of the iPhone, the number of smartphone users is steadily increasing.